Education: Insights from data
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Transcript of Education: Insights from data
INSIGHTS FROM DATA
DETECT ANOMALIES
Richard QuinnStrategic Management, UCF
“The exam was running at a grade and a half higher than it had ever run before... You don’t see that kind of grade improvement by chance.”
Series1
Series1
Summer2010
Mid-term
Fall2010
Mid-term
“A bimodal distribution exists when an external force is applied to the dataset that creates a systematic bias.”
SEE THE REAL IMPACT OF POLICY
ENGLISH
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SOCIAL SCIENCE
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LANGUAGE
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SCIENCE
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MATHEMATICS
1 5.5%2 4.3%3 2.3%4 0.9%5 0.3%6 0.1%
MATHEMATICS 3.08%COMMERCE 0.80%ACCOUNTANCY 0.33%PHYSICS 0.26%ECONOMICS 0.21%HISTORY 0.19%
How many subjects do students fail in?What contributes to single failures?
PHYSICS MATHEMATICS 0.79%PHYSICS CHEMISTRY 0.77%CHEMISTRY MATHEMATICS 0.55%COMMERCE ACCOUNTANCY 0.29%ENGLISH COMMERCE 0.17%BIOLOGY MATHEMATICS 0.14%
Two-subject failures
WHAT DETERMINES PERFORMANCE?
Subject Girs higher by Girls BoysPhysics 0 119 119Chemistry 1 123 122English 4 130 126Computers 6 137 131Biology 6 129 123Mathematics 11 123 112Language 11 152 141Accounting 12 138 126Commerce 13 127 114Economics 16 142 126
PERFORMANCE: GIRLS VS BOYS
Based on the results of the 20 lakh students taking the Class XII exams at Tamil Nadu over the last 3 years, it appears that the month you were born in can make a difference of as much as 120 marks out of 1,200.
June borns score the
lowest
The marks shoot up for Aug borns
… and peaks for Sep-borns
120 marks out of 1200
explainable by month of birth
An identical pattern was observed in 2009 and 2010…
… and across districts, gender, subjects, and class X & XII.
“It’s simply that in Canada the eligibility cutoff for age-class hockey is January 1. A boy who turns ten on January 2, then, could be playing alongside someone who doesn’t turn ten until the end of the year—and at that age, in preadolescence, a twelve-month gap in age represents an enormous difference in physical maturity.”
-- Malcolm Gladwell, Outliers
BIG DATA REQUIRES RICHER VISUALS
MONITORING
EFFECTIVELY
MONITORING
EFFECTIVELY
Jain
Harini
Shweta
Sneha Pooja
Ashwin
Shah
Deepti
Sanjana
Varshini
Ezhumalai
Venkatesan
Silambarasan
Pandiyan
Kumaresan
Manikandan
Thirupathi
Agarwal
Kumar
Priya
FIND HIDDEN CORRELATIONS
COMPARING PERFORMANCE
EMBRACE AND LEARN FROM DATA
USE IT TO DRIVE YOUR DECISIONS